extension_utils.py 23.6 KB
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# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import os
import re
import six
import sys
import copy
import glob
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import logging
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import collections
import textwrap
import warnings
import subprocess

from contextlib import contextmanager
from setuptools.command import bdist_egg

from .. import load_op_library
from ...fluid import core
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from ...fluid.framework import OpProtoHolder
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from ...sysconfig import get_include, get_lib

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logging.basicConfig(
    format='%(asctime)s - %(levelname)s - %(message)s', level=logging.INFO)
logger = logging.getLogger("utils.cpp_extension")

OS_NAME = sys.platform
IS_WINDOWS = OS_NAME.startswith('win')
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NVCC_COMPILE_FLAGS = [
    '-ccbin', 'cc', '-DPADDLE_WITH_CUDA', '-DEIGEN_USE_GPU', '-DPADDLE_USE_DSO',
    '-Xcompiler', '-fPIC', '-w', '--expt-relaxed-constexpr', '-O3', '-DNVCC'
]

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GCC_MINI_VERSION = (5, 4, 0)
# Give warning if using wrong compiler
WRONG_COMPILER_WARNING = '''
                        *************************************
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                        *  Compiler Compatibility WARNING   *
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                        *************************************

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

Found that your compiler ({user_compiler}) is not compatible with the compiler 
built Paddle for this platform, which is {paddle_compiler} on {platform}. Please
use {paddle_compiler} to compile your custom op. Or you may compile Paddle from
source using {user_compiler}, and then also use it compile your custom op.

See https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/2.0/install/compile/linux-compile.html
for help with compiling Paddle from source.

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
'''
# Give warning if used compiler version is incompatible
ABI_INCOMPATIBILITY_WARNING = '''
                            **********************************
                            *    ABI Compatibility WARNING   *
                            **********************************

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

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Found that your compiler ({user_compiler} == {version}) may be ABI-incompatible with pre-installed Paddle!
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Please use compiler that is ABI-compatible with GCC >= 5.4 (Recommended 8.2).

See https://gcc.gnu.org/onlinedocs/libstdc++/manual/abi.html for ABI Compatibility
information

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
'''
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USING_NEW_CUSTOM_OP_LOAD_METHOD = True


# NOTE(chenweihang): In order to be compatible with 
# the two custom op define method, after removing 
# old method, we can remove them together
def use_new_custom_op_load_method(*args):
    global USING_NEW_CUSTOM_OP_LOAD_METHOD
    if len(args) == 0:
        return USING_NEW_CUSTOM_OP_LOAD_METHOD
    else:
        assert len(args) == 1 and isinstance(args[0], bool)
        USING_NEW_CUSTOM_OP_LOAD_METHOD = args[0]

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@contextmanager
def bootstrap_context():
    """
    Context to manage how to write `__bootstrap__` code in .egg
    """
    origin_write_stub = bdist_egg.write_stub
    bdist_egg.write_stub = custom_write_stub
    yield

    bdist_egg.write_stub = origin_write_stub


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def load_op_meta_info_and_register_op(lib_filename):
    if USING_NEW_CUSTOM_OP_LOAD_METHOD:
        core.load_op_meta_info_and_register_op(lib_filename)
    else:
        print("old branch")
        core.load_op_library(lib_filename)
    return OpProtoHolder.instance().update_op_proto()


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def custom_write_stub(resource, pyfile):
    """
    Customized write_stub function to allow us to inject generated python
    api codes into egg python file.
    """
    _stub_template = textwrap.dedent("""
        import os
        import sys
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        import types
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        import paddle
        
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        def inject_ext_module(module_name, api_names):
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            if module_name in sys.modules:
                return sys.modules[module_name]

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            new_module = types.ModuleType(module_name)
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            for api_name in api_names:
                setattr(new_module, api_name, eval(api_name))
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            return new_module

        def __bootstrap__():
            cur_dir = os.path.dirname(os.path.abspath(__file__))
            so_path = os.path.join(cur_dir, "{resource}")

            assert os.path.exists(so_path)

            # load custom op shared library with abs path
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            new_custom_ops = paddle.utils.cpp_extension.load_op_meta_info_and_register_op(so_path)
            m = inject_ext_module(__name__, new_custom_ops)
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        __bootstrap__()

        {custom_api}
        """).lstrip()

    # Parse registerring op information
    _, op_info = CustomOpInfo.instance().last()
    so_path = op_info.build_directory

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    new_custom_ops = load_op_meta_info_and_register_op(so_path)
    assert len(
        new_custom_ops
    ) > 0, "Required at least one custom operators, but received len(custom_op) =  %d" % len(
        new_custom_ops)
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    # NOTE: To avoid importing .so file instead of python file because they have same name,
    # we rename .so shared library to another name, see EasyInstallCommand.
    filename, ext = os.path.splitext(resource)
    resource = filename + "_pd_" + ext

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    api_content = []
    for op_name in new_custom_ops:
        api_content.append(_custom_api_content(op_name))

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    with open(pyfile, 'w') as f:
        f.write(
            _stub_template.format(
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                resource=resource, custom_api='\n\n'.join(api_content)))
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OpInfo = collections.namedtuple('OpInfo',
                                ['so_name', 'build_directory', 'out_dtypes'])


class CustomOpInfo:
    """
    A global Singleton map to record all compiled custom ops information.
    """

    @classmethod
    def instance(cls):
        if not hasattr(cls, '_instance'):
            cls._instance = cls()
        return cls._instance

    def __init__(self):
        assert not hasattr(
            self.__class__,
            '_instance'), 'Please use `instance()` to get CustomOpInfo object!'
        # NOTE(Aurelius84): Use OrderedDict to save more order information
        self.op_info_map = collections.OrderedDict()

    def add(self, op_name, so_name, build_directory=None, out_dtypes=None):
        self.op_info_map[op_name] = OpInfo(so_name, build_directory, out_dtypes)

    def last(self):
        """
        Return the lastest insert custom op info.
        """
        assert len(self.op_info_map) > 0
        return next(reversed(self.op_info_map.items()))


def prepare_unix_cflags(cflags):
    """
    Prepare all necessary compiled flags for nvcc compiling CUDA files.
    """
    cflags = NVCC_COMPILE_FLAGS + cflags + get_cuda_arch_flags(cflags)

    return cflags


def add_std_without_repeat(cflags, compiler_type, use_std14=False):
    """
    Append -std=c++11/14 in cflags if without specific it before.
    """
    cpp_flag_prefix = '/std:' if compiler_type == 'msvc' else '-std='
    if not any(cpp_flag_prefix in flag for flag in cflags):
        suffix = 'c++14' if use_std14 else 'c++11'
        cpp_flag = cpp_flag_prefix + suffix
        cflags.append(cpp_flag)


def get_cuda_arch_flags(cflags):
    """
    For an arch, say "6.1", the added compile flag will be
    ``-gencode=arch=compute_61,code=sm_61``.
    For an added "+PTX", an additional
    ``-gencode=arch=compute_xx,code=compute_xx`` is added.
    """
    # TODO(Aurelius84):
    return []


def normalize_extension_kwargs(kwargs, use_cuda=False):
    """ 
    Normalize include_dirs, library_dir and other attributes in kwargs.
    """
    assert isinstance(kwargs, dict)
    # append necessary include dir path of paddle
    include_dirs = kwargs.get('include_dirs', [])
    include_dirs.extend(find_paddle_includes(use_cuda))
    kwargs['include_dirs'] = include_dirs

    # append necessary lib path of paddle
    library_dirs = kwargs.get('library_dirs', [])
    library_dirs.extend(find_paddle_libraries(use_cuda))
    kwargs['library_dirs'] = library_dirs

    # add runtime library dirs
    runtime_library_dirs = kwargs.get('runtime_library_dirs', [])
    runtime_library_dirs.extend(find_paddle_libraries(use_cuda))
    kwargs['runtime_library_dirs'] = runtime_library_dirs

    # append compile flags
    extra_compile_args = kwargs.get('extra_compile_args', [])
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    extra_compile_args.extend(['-g', '-w'])  # diable warnings
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    kwargs['extra_compile_args'] = extra_compile_args

    # append link flags
    extra_link_args = kwargs.get('extra_link_args', [])
    extra_link_args.extend(['-lpaddle_framework', '-lcudart'])
    kwargs['extra_link_args'] = extra_link_args

    kwargs['language'] = 'c++'
    return kwargs


def find_paddle_includes(use_cuda=False):
    """
    Return Paddle necessary include dir path.
    """
    # pythonXX/site-packages/paddle/include
    paddle_include_dir = get_include()
    third_party_dir = os.path.join(paddle_include_dir, 'third_party')

    include_dirs = [paddle_include_dir, third_party_dir]

    return include_dirs


def find_cuda_includes():

    cuda_home = find_cuda_home()
    if cuda_home is None:
        raise ValueError(
            "Not found CUDA runtime, please use `export CUDA_HOME=XXX` to specific it."
        )

    return [os.path.join(cuda_home, 'lib64')]


def find_cuda_home():
    """
    Use heuristic method to find cuda path
    """
    # step 1. find in $CUDA_HOME or $CUDA_PATH
    cuda_home = os.environ.get('CUDA_HOME') or os.environ.get('CUDA_PATH')

    # step 2.  find path by `which nvcc`
    if cuda_home is None:
        which_cmd = 'where' if IS_WINDOWS else 'which'
        try:
            with open(os.devnull, 'w') as devnull:
                nvcc_path = subprocess.check_output(
                    [which_cmd, 'nvcc'], stderr=devnull)
                if six.PY3:
                    nvcc_path = nvcc_path.decode()
                nvcc_path = nvcc_path.rstrip('\r\n')
                # for example: /usr/local/cuda/bin/nvcc
                cuda_home = os.path.dirname(os.path.dirname(nvcc_path))
        except:
            if IS_WINDOWS:
                # search from default NVIDIA GPU path
                candidate_paths = glob.glob(
                    'C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v*.*')
                if len(candidate_paths) > 0:
                    cuda_home = candidate_paths[0]
            else:
                cuda_home = "/usr/local/cuda"
    # step 3. check whether path is valid
    if not os.path.exists(cuda_home) and core.is_compiled_with_cuda():
        cuda_home = None
        warnings.warn(
            "Not found CUDA runtime, please use `export CUDA_HOME= XXX` to specific it."
        )

    return cuda_home


def find_paddle_libraries(use_cuda=False):
    """
    Return Paddle necessary library dir path.
    """
    # pythonXX/site-packages/paddle/libs
    paddle_lib_dirs = [get_lib()]
    if use_cuda:
        cuda_dirs = find_cuda_includes()
        paddle_lib_dirs.extend(cuda_dirs)
    return paddle_lib_dirs


def add_compile_flag(extension, flag):
    extra_compile_args = copy.deepcopy(extension.extra_compile_args)
    if isinstance(extra_compile_args, dict):
        for args in extra_compile_args.values():
            args.append(flag)
    else:
        extra_compile_args.append(flag)

    extension.extra_compile_args = extra_compile_args


def is_cuda_file(path):

    cuda_suffix = set(['.cu'])
    items = os.path.splitext(path)
    assert len(items) > 1
    return items[-1] in cuda_suffix


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def get_build_directory(verbose=False):
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    """
    Return paddle extension root directory, default specific by `PADDLE_EXTENSION_DIR`
    """
    root_extensions_directory = os.environ.get('PADDLE_EXTENSION_DIR')
    if root_extensions_directory is None:
        dir_name = "paddle_extensions"
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        if OS_NAME.startswith('linux'):
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            root_extensions_directory = os.path.join(
                os.path.expanduser('~/.cache'), dir_name)
        else:
            # TODO(Aurelius84): consider wind32/macOs
            raise NotImplementedError("Only support Linux now.")

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        log_v("$PADDLE_EXTENSION_DIR is not set, using path: {} by default.".
              format(root_extensions_directory), verbose)
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    if not os.path.exists(root_extensions_directory):
        os.makedirs(root_extensions_directory)

    return root_extensions_directory


def parse_op_info(op_name):
    """
    Parse input names and outpus detail information from registered custom op
    from OpInfoMap.
    """
    from paddle.fluid.framework import OpProtoHolder
    if op_name not in OpProtoHolder.instance().op_proto_map:
        raise ValueError(
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            "Please load {} shared library file firstly by `paddle.utils.cpp_extension.load_op_meta_info_and_register_op(...)`".
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            format(op_name))
    op_proto = OpProtoHolder.instance().get_op_proto(op_name)

    in_names = [x.name for x in op_proto.inputs]
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    out_names = [x.name for x in op_proto.outputs]
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    return in_names, out_names
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def _import_module_from_library(module_name, build_directory, verbose=False):
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    """
    Load .so shared library and import it as callable python module.
    """
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    # TODO(Aurelius84): Consider file suffix is .dll on Windows Platform.
    ext_path = os.path.join(build_directory, module_name + '.so')
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    if not os.path.exists(ext_path):
        raise FileNotFoundError("Extension path: {} does not exist.".format(
            ext_path))

    # load custom op_info and kernels from .so shared library
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    log_v('loading shared library from: {}'.format(ext_path), verbose)
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    op_names = load_op_meta_info_and_register_op(ext_path)
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    # generate Python api in ext_path
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    return _generate_python_module(module_name, op_names, build_directory,
                                   verbose)
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def _generate_python_module(module_name,
                            op_names,
                            build_directory,
                            verbose=False):
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    """
    Automatically generate python file to allow import or load into as module
    """
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    api_file = os.path.join(build_directory, module_name + '.py')
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    log_v("generate api file: {}".format(api_file), verbose)
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    # write into .py file
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    api_content = [_custom_api_content(op_name) for op_name in op_names]
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    with open(api_file, 'w') as f:
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        f.write('\n\n'.join(api_content))
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    # load module
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    custom_module = _load_module_from_file(api_file, verbose)
    return custom_module
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def _custom_api_content(op_name):
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    params_str, ins_str, outs_str = _get_api_inputs_str(op_name)
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    API_TEMPLATE = textwrap.dedent("""
        from paddle.fluid.layer_helper import LayerHelper

        def {op_name}({inputs}):
            helper = LayerHelper("{op_name}", **locals())

            # prepare inputs and output 
            ins = {ins}
            outs = {{}}
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            out_names = {out_names}
            for out_name in out_names:
                # Set 'float32' temporarily, and the actual dtype of output variable will be inferred
                # in runtime.
                outs[out_name] = helper.create_variable(dtype='float32')
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            helper.append_op(type="{op_name}", inputs=ins, outputs=outs)

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            res = [outs[out_name] for out_name in out_names]

            return res[0] if len(res)==1 else res
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            """).lstrip()

    # generate python api file
    api_content = API_TEMPLATE.format(
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        op_name=op_name, inputs=params_str, ins=ins_str, out_names=outs_str)
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    return api_content


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def _load_module_from_file(api_file_path, verbose=False):
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    """
    Load module from python file.
    """
    if not os.path.exists(api_file_path):
        raise FileNotFoundError("File : {} does not exist.".format(
            api_file_path))

    # Unique readable module name to place custom api.
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    log_v('import module from file: {}'.format(api_file_path), verbose)
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    ext_name = "_paddle_cpp_extension_"
    if six.PY2:
        import imp
        module = imp.load_source(ext_name, api_file_path)
    else:
        from importlib import machinery
        loader = machinery.SourceFileLoader(ext_name, api_file_path)
        module = loader.load_module()

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    return module
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def _get_api_inputs_str(op_name):
    """
    Returns string of api parameters and inputs dict.
    """
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    in_names, out_names = parse_op_info(op_name)
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    # e.g: x, y, z
    params_str = ','.join([p.lower() for p in in_names])
    # e.g: {'X': x, 'Y': y, 'Z': z}
    ins_str = "{%s}" % ','.join(
        ["'{}' : {}".format(in_name, in_name.lower()) for in_name in in_names])
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    # e.g: ['Out', 'Index']
    outs_str = "[%s]" % ','.join(["'{}'".format(name) for name in out_names])
    return params_str, ins_str, outs_str
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def _write_setup_file(name,
                      sources,
                      file_path,
                      include_dirs,
                      compile_flags,
                      link_args,
                      verbose=False):
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    """
    Automatically generate setup.py and write it into build directory.
    """
    template = textwrap.dedent("""
    import os
    from paddle.utils.cpp_extension import CppExtension, CUDAExtension, BuildExtension, setup
    from paddle.utils.cpp_extension import get_build_directory
    setup(
        name='{name}',
        ext_modules=[
            {prefix}Extension(
                name='{name}',
                sources={sources},
                include_dirs={include_dirs},
                extra_compile_args={extra_compile_args},
                extra_link_args={extra_link_args})],
        cmdclass={{"build_ext" : BuildExtension.with_options(
            output_dir=get_build_directory(),
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            no_python_abi_suffix=True,
            use_new_method={use_new_method})
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        }})""").lstrip()

    with_cuda = False
    if any([is_cuda_file(source) for source in sources]):
        with_cuda = True
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    log_v("with_cuda: {}".format(with_cuda), verbose)
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    content = template.format(
        name=name,
        prefix='CUDA' if with_cuda else 'Cpp',
        sources=list2str(sources),
        include_dirs=list2str(include_dirs),
        extra_compile_args=list2str(compile_flags),
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        extra_link_args=list2str(link_args),
        use_new_method=use_new_custom_op_load_method())
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    log_v('write setup.py into {}'.format(file_path), verbose)
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    with open(file_path, 'w') as f:
        f.write(content)


def list2str(args):
    """
    Convert list[str] into string. For example: [x, y] -> "['x', 'y']"
    """
    if args is None: return '[]'
    assert isinstance(args, (list, tuple))
    args = ["'{}'".format(arg) for arg in args]
    return '[' + ','.join(args) + ']'


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def _jit_compile(file_path, interpreter=None, verbose=False):
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    """
    Build shared library in subprocess
    """
    ext_dir = os.path.dirname(file_path)
    setup_file = os.path.basename(file_path)
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    if interpreter is None:
        interpreter = 'python'
    try:
        py_path = subprocess.check_output(['which', interpreter])
        py_version = subprocess.check_output([interpreter, '-V'])
        if six.PY3:
            py_path = py_path.decode()
            py_version = py_version.decode()
        log_v("Using Python interpreter: {}, version: {}".format(
            py_path.strip(), py_version.strip()), verbose)
    except Exception:
        _, error, _ = sys.exc_info()
        raise RuntimeError(
            'Failed to check Python interpreter with `{}`, errors: {}'.format(
                interpreter, error))

    compile_cmd = 'cd {} && {} {} build'.format(ext_dir, interpreter,
                                                setup_file)
    print("Compiling user custom op, it will cost a few seconds.....")
    run_cmd(compile_cmd, verbose)
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def parse_op_name_from(sources):
    """
    Parse registerring custom op name from sources.
    """

    def regex(content):
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        if USING_NEW_CUSTOM_OP_LOAD_METHOD:
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            pattern = re.compile(r'PD_BUILD_OP\(([^,\)]+)\)')
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        else:
            pattern = re.compile(r'REGISTER_OPERATOR\(([^,]+),')
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        content = re.sub(r'\s|\t|\n', '', content)
        op_name = pattern.findall(content)
        op_name = set([re.sub('_grad', '', name) for name in op_name])

        return op_name

    op_names = set()
    for source in sources:
        with open(source, 'r') as f:
            content = f.read()
            op_names |= regex(content)

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    return list(op_names)
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def run_cmd(command, verbose=False):
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    """
    Execute command with subprocess.
    """
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    # logging
    log_v("execute command: {}".format(command), verbose)
    try:
        from subprocess import DEVNULL  # py3
    except ImportError:
        DEVNULL = open(os.devnull, 'wb')

    # execute command
    try:
        if verbose:
            return subprocess.check_call(
                command, shell=True, stderr=subprocess.STDOUT)
        else:
            return subprocess.check_call(command, shell=True, stdout=DEVNULL)
    except Exception:
        _, error, _ = sys.exc_info()
        raise RuntimeError("Failed to run command: {}, errors: {}".format(
            compile, error))


def check_abi_compatibility(compiler, verbose=False):
    """
    Check whether GCC version on user local machine is compatible with Paddle in
    site-packages.
    """
    # TODO(Aurelius84): After we support windows, remove IS_WINDOWS in following code.
    if os.environ.get('PADDLE_SKIP_CHECK_ABI') in ['True', 'true', '1'
                                                   ] or IS_WINDOWS:
        return True

    cmd_out = subprocess.check_output(
        ['which', compiler], stderr=subprocess.STDOUT)
    compiler_path = os.path.realpath(cmd_out.decode()
                                     if six.PY3 else cmd_out).strip()
    # step 1. if not found any suitable compiler, raise error
    if not any(name in compiler_path
               for name in _expected_compiler_current_platform()):
        warnings.warn(
            WRONG_COMPILER_WARNING.format(
                user_compiler=compiler,
                paddle_compiler=_expected_compiler_current_platform()[0],
                platform=OS_NAME))
        return False

    # clang++ have no ABI compatibility problem
    if OS_NAME.startswith('darwin'):
        return True
    try:
        if OS_NAME.startswith('linux'):
            version_info = subprocess.check_output(
                [compiler, '-dumpfullversion'])
            if six.PY3:
                version_info = version_info.decode()
            version = version_info.strip().split('.')
            assert len(version) == 3
            # check version compatibility
            if tuple(map(int, version)) >= GCC_MINI_VERSION:
                return True
            else:
                warnings.warn(
                    ABI_INCOMPATIBILITY_WARNING.format(
                        user_compiler=compiler, version=version_info.strip()))
        # TODO(Aurelius84): check version compatibility on windows
        elif IS_WINDOWS:
            warnings.warn("We don't support Windows now.")
    except Exception:
        _, error, _ = sys.exc_info()
        warnings.warn('Failed to check compiler version for {}: {}'.format(
            compiler, error))

    return False


def _expected_compiler_current_platform():
    """
    Returns supported compiler string on current platform
    """
    expect_compilers = ['clang', 'clang++'] if OS_NAME.startswith(
        'darwin') else ['gcc', 'g++', 'gnu-c++', 'gnu-cc']
    return expect_compilers


def log_v(info, verbose):
    """
    Print log information on stdout.
    """
    if verbose:
        logging.info(info)